diff --git a/src/llama-sampling.cpp b/src/llama-sampling.cpp
index 7b48e5d970..7684c8f38c 100644
--- a/src/llama-sampling.cpp
+++ b/src/llama-sampling.cpp
@@ -2365,22 +2365,6 @@ static const char * llama_sampler_power_law_name(const struct llama_sampler * /*
     return "power-law";
 }
 
-// compute the adapted target probability for the current sampling step
-static float llama_sampler_power_law_compute_target(const llama_sampler_power_law * ctx) {
-    const float base_target = ctx->target;
-    if (ctx->total_weight == 0.0f) {
-        fprintf(stderr, "power-law: compute_target: total_weight == 0.0 (target fixed at %.3f)\n", base_target); fflush(stderr);
-        return base_target;
-    }
-    float target = 2.0f * base_target - (ctx->weighted_sum / ctx->total_weight);
-    fprintf(stderr, "power-law: compute_target: raw target = %.3f\n", target);
-
-    // clamp result to [0.0, 1.0]
-    target = std::clamp(target, 0.0f, 1.0f);
-    fprintf(stderr, "power-law: compute_target: clamped target = %.3f\n", target); fflush(stderr);
-    return target;
-}
-
 static void llama_sampler_power_law_apply(struct llama_sampler * smpl, llama_token_data_array * cur_p) {
     auto * ctx = (llama_sampler_power_law *) smpl->ctx;
 
@@ -2400,13 +2384,18 @@ static void llama_sampler_power_law_apply(struct llama_sampler * smpl, llama_tok
         ctx->original_probs[i] = cur_p->data[i].p;
     }
 
-    float computed_target = llama_sampler_power_law_compute_target(ctx);
+    // compute the adapted target probability for the current sampling step
+    float computed_target = std::clamp(
+        ctx->total_weight == 0.0f ? ctx->target : 2.0f * ctx->target - (ctx->weighted_sum / ctx->total_weight),
+        0.0f, 1.0f
+    );
+    fprintf(stderr, "power-law: computed target = %.3f\n", computed_target);
 
     //
     // power law transform
     //
 
-    fprintf(stderr, "power-law: transform: cur_p->size = %d\n", (size_t)cur_p->size);
+    fprintf(stderr, "power-law: cur_p->size = %d\n", (int)cur_p->size);
     for (size_t i = 0; i < cur_p->size; ++i) {
         float dist = (cur_p->data[i].p - computed_target) * INV_WIDTH;
         cur_p->data[i].logit = PEAK_LOGIT_VALUE / (1.0f + dist * dist);
@@ -2421,7 +2410,6 @@ static void llama_sampler_power_law_apply(struct llama_sampler * smpl, llama_tok
 
     // update running history with the original probability of the selected token
     float original_p  = ctx->original_probs[idx];
-    fprintf(stderr, "power-law: original prob was %.3f\n", original_p);
     ctx->weighted_sum = original_p + ctx->decay * ctx->weighted_sum;
     fprintf(stderr, "power-law: updated ctx->weighted_sum = %.3f\n", ctx->weighted_sum);
     ctx->total_weight = 1.0f + ctx->decay * ctx->total_weight;